Multiple change-point detection for non-stationary time series using Wild Binary Segmentation
From MaRDI portal
Publication:137162
DOI10.5705/ss.202015.0262zbMath1356.62143OpenAlexW2189029542MaRDI QIDQ137162
Piotr Fryzlewicz, Karolos Korkas, Piotr Fryzlewicz, Karolos K. Korkas
Publication date: 2017
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: http://eprints.lse.ac.uk/64863/8/Fryzlewicz_Multiple%20change-point%20detection_2017_published%20LSERO.pdf
Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)
Related Items (10)
Detecting possibly frequent change-points: wild binary segmentation 2 and steepest-drop model selection ⋮ Detection of multiple change-points in the scale parameter of a gamma distributed sequence based on reversible jump MCMC ⋮ Data-driven estimation of change-points with mean shift ⋮ Detection of Multiple Structural Breaks in Large Covariance Matrices ⋮ Multiple change point detection and validation in autoregressive time series data ⋮ Asymptotic properties of \(M\)-estimators based on estimating equations and censored data in semi-parametric models with multiple change points ⋮ Ensemble Binary Segmentation for irregularly spaced data with change-points ⋮ wbsts ⋮ Detection of multiple change points for linear processes under negatively super-additive dependence ⋮ Asymptotic properties of semiparametric \(M\)-estimators with multiple change points
Uses Software
This page was built for publication: Multiple change-point detection for non-stationary time series using Wild Binary Segmentation
